Building Dynamic Image Collections from Internet

People often want to collect and utilize free,
publicly available images on a given subject.
Image sharing systems such as Flickr store
billions of user-contributed images. While
such systems are designed to encourage user
contributions and sharing, they are not well-
organized collections on any given subject.
We propose an approach that systematically
harvest images from Internet and organize the
images into an evolving faceted classification.
We implemented a prototype to continuously
harvest the most popular images on Flickr
related to African American history, and
organize them into an evolving faceted
classification collaboratively maintained by
users. The same approach can be applied
to other digital humanities resources on the
Internet. The talk will elaborate the details of
technical design and prototype implementation,
and discuss evaluation results.
2. Introduction
Flickr hosted over 4 billion images as of
October 2009 and is growing by about 4
million pictures a day. Facebook hosted 15
billion photos and Imageshack hosted 20 billion
images as of April 2009. Other photo sharing
sites such as Picasa, Multiply and PhotoBucket
also host billions of images [Schonfeld, 2009].
In contrast, organized public domain image
collections are relatively scarce [Wikipedia:
'Public domain image resources']. The largest
public domain image repository, Wikimedia
Commons, reached 5 million images as of
September 2009.
It would greatly benefit the humanities
community if images in those image sharing
sites can be organized and utilized. We propose
an approach that systematically searches and
harvests images (actually the link to the
image and metadata, but not image itself)
from image sharing sites, and organizes the
images into a multi-faceted classification. The
data harvesting is performed on a continual
basis, and the classification evolves over time.
Besides automated programs, the approach
utilizes collaborative human efforts to improve
the quality of collection. We implemented a
prototype that builds a dynamic image collection
on African American History from the most
popular images on this subject on Flickr.com.
Our fundamental belief is that a large, diverse
group of people (students, teachers, etc.) can
do better than a small team of librarians or
editors in constructing a multimedia collection
at virtually no cost.
Note that not all the images on those sharing
sites are copyright-free or have a creative
commons license. However, most of the sites
allow other websites to directly link to their
images if the images are marked as public access
by their contributors, and if credits are properly
given. Our approach displays images through
embedded image URLs but does not download
the images from their original sources.
3. Related Work
Many are trying to utilize the images in fast-
growing photo sharing and social networking
sites. For example Getty Images, the leader in
stock photography, hires image editors to select
most popular Flickr images and obtain copyright
from individual contributors, then sells the
images for $5 per image (
http://www.gettyim
ages.com/
). Computer-graphics researchers at
the University of Washington have utilized Web
images to digitally reconstruct buildings in 3-
D. For example, based on 150,000 publicly
accessible Flickr pictures of Rome, the program
automatically re-created the Colosseum, Trevi
Fountain, and the outside and inside of St.
Peter's Basilica, among other Roman icons.
The technique can be used to make virtual-
reality experiences for tourism, auto-build cities

2
for video games and movies, or help digitally
preserve and study historic cities that are being
destroyed by human-caused or environmental
factors [Jaggard 2009].
Researchers have argued for building an
academic Flickr, or an academic photo sharing
site in general: a net-based service that would
enable faculty and researchers to post and
share images with scholarly value, either with
the general community, or pursuant to any
associated rights, to restricted-use populations
[P. Brantley's blog]. For example, a group at
Lewis & Clark College in Portland is in the
process of developing an educational collection
of contemporary ceramics images using the
photo sharing site Flickr [McWilliams 2008].
Our project attempts to build free, well-
organized topical images collections from the
images contributed by Internet users, to support
education or research objectives. While most
photo sharing systems support keyword-based
search utilizing user-contributed metadata,
none of them support browsable hierarchies
that allow users to explore a given subject
in depth. Using librarians or images editors
to manually construct a topical collection is
cost prohibitive, and unfeasible if the collection
needs to keep up with rapidly growing data
sources. Our collection-construction approach
combines the collaborative concepts of wiki
and social tagging systems with automated
classification techniques. Our system allows
users to collaboratively build a classification
schema with multi-faceted categories, and to
classify documents into this schema. Utilizing
users’ manual efforts as training data, the
system’s automated techniques build a faceted
classification that evolves with the growing
collection, the expanding user base, and the
shifting user interests.
4. Architecture and Prototype
Implementation
Our collection construction approach is
summarized in Figure 1. The system first
collects images (links and metadata such as
tags) on a given topic using keyword search,
utilizing the APIs (Application Programming
Interface) provided by image sharing sites or
search engines. For the initial collection, a
group of experts or administrators create the
initial classification schema and classify a set
of images into the initial schema. Utilizing
experts’ classifications as training data, and also
Wordnet and Wikipedia as knowledge bases,
the system employs automated techniques
(heuristic matching rules and support vector
machine-based classifiers) to classify images
into the classification schema. In a wiki fashion,
users of the image collection can modify
and improve the classification schema, and
manually classify items into the schema. Users
can also assign additional tag or annotations to
image objects. Utilizing the additional metadata
from users’ tagging and annotation efforts and
by analyzing users’ classification/usage history,
the system refines both the classification schema
and the item-category associations. The system
continues to collect and classify images to stay
up-to-date with external image sources.
Figure 1. Systematic approach of constructing
a topical collection using Internet images.
We built a prototype to construct an image
collection on African American History from
Flickr. By querying “African American History”
in the search field, we extracted metadata
for all the images in the result pages: title,
url, description, tags, and the contributor. The
initial collection contained about 11,000 Flickr
images on African American History. Over 3
months the collection has grown to contain
about 13,000 images. During the conference we
will elaborate the details of technical design,
prototype implementation, and the evaluation
results. Figure 2 shows the browsing and
classification interfaces of our prototype.